Data mining at a regulatory agency to forecast waterflood recovery

Society of Petroleum Engineers - SPE Rocky Mountain Petroleum Technology Conference 2001, RMPTC 2001

Volumn , Issue , 2001, Pages

  Weiss, W W ^a   Wo, Shaochang ^b   Weiss, J W ^c   Weber, James ^d  

^a NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY   (United States)

^b Lasso Innovations   (United States)

^c SPE   (United States)

^d Coral Production Corporation ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUDITION; COMPUTER SYSTEM RECOVERY; DATA MINING; FORECASTING; FUZZY SETS; GASOLINE; LANDFORMS; RECOVERY; SECONDARY RECOVERY;

CORRELATION COEFFICIENT; FUZZY RANKINGS; NEBRASKA PANHANDLES; NETWORK CORRELATIONS; OIL RECOVERIES; PUBLIC INFORMATION; REGULATORY AGENCIES; TRAINED NEURAL NETWORKS;

OIL WELL FLOODING;

EID: 85054502038     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Smith, C.R.: Mechanics of Secondary Oil Recovery, Reinhold Publishing Corporation, New York, (1966) 2.
2. Mattax, C.C. and Dalton, R.L.: Reservoir Simulation, Monograph Series, SPE, Richardson TX (1980) 1.
3. Standard Handbook of Petroleum and Natural Gas Engineering, William C. Lyons (ed.) Gulf Publishing Company, Houston (1996) 277-278.
4. Haykin, S.: Neural Networks: A Comprehensive Foundation, Macmillan College Publishing Company, New York (1994).
5. Lin, Y. and Cunningham, G.A.III: "Identifying Significant Inputs Using Fuzzy Curves," Proceedings, Third International Conference on Fuzzy Systems, Orlando FL, June 26-29, 1994, p 2031-2036.
6. http://www-ra.informatik.uni-tuebingen.de/SNNS/